machine learning

right into a curious era of artificial intelligence where size is wrongly equated with intelligence. The models get larger and bigger to billions of parameters, the information centers grow to be industrial in...

has turn out to be the one only approach for me to resolve problems. Most problems I encounter at work might be solved effectively by utilizing agents. That is in contrast to manually...

landed on arXiv just before Christmas 2025, very much an early present from the team at Google DeepMind, with the title “Towards a Science of Scaling Agent Systems.” I discovered this paper to be a...

structured data right into a RAG system, engineers often default to embedding raw JSON right into a vector database. The fact, nonetheless, is that this intuitive approach results in dramatically poor performance. Modern...

of autonomous vehicles and AI language models, yet the predominant physical interface through which we connect with machines has remained unchanged for 50 years. Astonishingly, we're still using the pc mouse, a tool...

within the federated learning series I'm doing, and should you just landed here, I might recommend going through the primary part where we discussed how federated learning works at a high level. For...

forecasting errors are usually not brought on by bad time-series models. They're brought on by ignoring structure. SKUs don't behave independently. They interact through shared plants, product groups, warehouses, and storage locations. A requirement shock...

, the thought has circulated within the AI field that prompt engineering is dead, or not less than obsolete. This, on one side because pure language models have turn out to be more flexible...